Spatial mode adaptation at the cell edge using interferer spatial correlation

ABSTRACT

A system and method is proposed for adapting the spatial transmission strategy in a cellular MIMO (multiple input multiple output) communication system for the downlink. Spatial mode adaptation, the choice of multiplexing, transmit diversity, number of streams, space-time code family, and the like are performed slowly based on side information from other base stations. Base stations exchange their transmission plans with neighboring base stations and broadcast this information to active users. Each user measures its susceptibility to spatial interference and returns this information to the base station. The base station then schedules active users according to the decisions made in interfering base stations and the preferred transmission strategies of its own users.

This application is a divisional of U.S. patent application Ser. No.12/125,604, entitled “Spatial Mode Adaptation at the Cell Edge UsingInterferer Spatial Correlation,” filed on May 22, 2008, whichapplication is hereby incorporated herein by reference.

TECHNICAL FIELD

The present invention relates, in general, to wireless communicationssystems, and, more particularly, to adapting how data is transmitted tousers that experience interference in a system with a plurality oftransmit antennas.

BACKGROUND

Multiple-input multiple-output (MIMO) technology exploits the spatialcomponents of the wireless channel to provide capacity gain andincreased link robustness. After almost a decade of research, MIMOwireless communication has finally been adopted in several standardsincluding IEEE 802.16e-2005 and IEEE 802.11n; products based on draftstandards are already shipping. MIMO is often combined with OFDM(orthogonal frequency division multiplexing), a type of digitalmodulation that makes it easy to equalize broadband channels.

In MIMO communication systems, at the transmitter, data are modulated,encoded, and mapped onto spatial signals, which are transmitted frommultiple transmit antennas. A main difference with non-MIMOcommunication systems is that there are many different spatialformatting modes for example beamforming, precoding, spatialmultiplexing, space-time coding, and limited feedback precoding, amongothers (see A. Paulraj, R. Nabar, and D. Gore, Introduction toSpace-Time Wireless Communications. 40 West 20th Street, New York, N.Y.,USA: Cambridge University Press, 2003 and the references within). Thespatial formatting techniques have different performance (in terms ofcapacity, goodput, achievable rate, or bit error rate for example) indifferent channel environments. Consequently, an advantageous componentof MIMO wireless systems is adapting the transmitted rate in response tochannel conditions in what is known as space-time adaptation, linkadaptation, or adaptive space-time modulation.

In MIMO communication systems, space-time link adaptation involvesadapting the transmitter in response to channel quality information tomaximize a performance measure. As one example, prior work considers thejoint adaptation of the modulation and coding rate with the spatialformatting to achieve a target performance measure. For example, asdescribed in (R. Heath and A. Paulraj, “Switching between diversity andmultiplexing in MIMO systems,” IEEE Trans. Commun., vol. 53, no. 6, pp.962-968, 2005) the transmitter may switch between a spatial multiplexingspatial formatting method and a spatial diversity spatial formattingmethod. As described in (S. Catreux, V. Erceg, D. Gesbert, and Heath, R.W., “Adaptive modulation and MIMO coding for broadband wireless datanetworks,” IEEE Commun. Mag., vol. 40, no. 6, pp. 108-115, 2002),switching between spatial formatting methods substantially improvesperformance in MIMO wireless communication systems. The high throughputadvantages of spatial multiplexing can be achieved when the spatialchannel is sufficiently rich while the robustness advantages of spatialdiversity can be achieved when the channel is severely fading.

Channel quality information is used to make adaptive modulation, coding,and spatial formatting decisions at the transmitter. Channel qualityinformation may be obtained using a method known as reciprocity wherethe transmit channel is inferred from the received channel estimate ormay be obtained through a feedback channel. When obtained through theuse of a feedback channel, channel quality information is computed frommeasurements made at the receiver. Many different types of channelquality indicators may be used to help make adaptation decisionsincluding signal strength, signal-to-noise ratio (SNR),single-to-interference-plus-noise ratio (SINR), quantized channel stateinformation, limited feedback channel state information, and channelcorrelation, for example. The receiver may also compute the preferredmodulation, coding, and spatial formatting mode and this may alsoconstitute channel quality information.

In prior work, the channel quality information may be used inconjunction with a spatial formatting table to determine the appropriatespatial format. For example, the method in R. Heath and A. Paulraj,“Switching between diversity and multiplexing in MIMO systems,” IEEETrans. Commun., vol. 53, no. 6, pp. 962-968, 2005, used one bit offeedback from the receiver to improve error rate performance for fixeddata rate transmission by switching between space-time block coding andspatial multiplexing. That approach can be combined with link adaptationin a straightforward fashion. The adaptive method in S. Catreux, V.Erceg, D. Gesbert, and Heath, R. W., “Adaptive modulation and MIMOcoding for broadband wireless data networks,” IEEE Commun. Mag., vol.40, no. 6, pp. 108-115, 2002, was designed to enhance spectralefficiency in MIMO-OFDM communication systems using channel qualityinformation in the form of statistical time/frequency selectivityindicators. Spatial correlation information has also been used toimplement link adaptation, as described in A. Forenza, M. R. McKay, A.Pandharipande, R. W. Heath, and I. B. Collings, “Adaptive MIMOtransmission for exploiting the capacity of spatially correlatedchannels,” IEEE Trans. Veh. Technol., vol. 56, no. 2, pp. 619-630, March2007 where statistical beamforming, spatial multiplexing, and doublespace-time block coding spatial formatting strategies are considered.When correlation based channel quality information is employed, thespatial formatting may be determined by the correlation, while themodulation and coding rate may be determine by other channel qualityinformation and may vary more quickly.

A key assumption in prior work on space-time adaptation, or modeswitching, is the absence of interference. Unfortunately, in mostcellular wireless systems, especially at the cell edge, thecommunication link is interference limited. In what is known as thedownlink of a cellular system, this means a subscriber being served inone cell receives a non-negligible amount of co-channel interferencefrom transmitters in other cells. The presence of interference reducesthe capacity and increases the bit error rate. This makes providingreasonable quality of service to users at the edge of the cell even morechallenging.

Typically interference is modeled as colored noise. To compensate forthis, receivers typically include a noise whitening filter, which isapplied to the received signal based on an estimate of the interferenceplus noise covariance. As a result, the channel estimated at thereceiver includes the effects of the whitening filter, and thus theeffects of interference are present in the estimated channel. Inwireless communication systems that do not employ MIMO communicationtechnology, the interference may be treated as additional noise power.The corresponding methods for link adaptation may still work in thissituation. Unfortunately, interference severely impacts performance inMIMO communication systems, especially when spatial multiplexing is used(see J. G. Andrews, W. Choi, and R. W. Heath, Jr., “OvercomingInterference in Multi-Antenna Cellular Networks,” IEEE WirelessCommunications, vol. 14, no. 6, pp. 95-104, December 2007). The reasonis that the spatial formatting method in a given wireless cell isimpacted by the choice of the spatial formatting method in theinterfering cells. This can lead to a competitive scenario where cellsupdate their spatial formatting methods in response to interference, butthey themselves create interference forcing neighboring cells to changetheir spatial formatting method and so on.

The problem of link adaptation in MIMO systems including the effects ofinterference has been addressed in some prior work. Reference J. H.Kotecha and J. C. Mundarath, “Non-Collaborative Zero-Forcing Beamformingin the Presence of Co-Channel Interference and Spatially CorrelatedChannels,” Proc. of Veh. Techn. Conf., September 2007. This paper alsodeals with interference in MIMO systems. It focuses on multi-user MIMOand does not allow any coordination between base stations. It simplyderives a statistical solution

Reference A. Szabo, N. Gengf, A. Klein, I. Viering, and J. A. Nossek,“On the performance of fast feedback and link adaptation for MIMOeigenbeamforming in cellular systems,” Proc. of the ITG Workshop onSmart Antennas, pp. 144-151, 2004, studies the impact of interference onspatial mode adaptation in MIMO cellular systems. It also recognizesthat even if statistical precoding is used at the transmitter, theoptimum rates will change as a function of the interference covariance.This prior work recognizes that there is mismatch but does not propose aconcrete solution to the problem of adapting in the presence of changingspatial interference.

Reference Shiming Liu, Xing Zhang, Wenbo Wang, “Analysis of Modulationand Coding Scheme Selection in MIMO-OFDM Systems,” Proc. of Int. Conf.on Comm. and Electronics, pp. 240-245, Oct. 10-11, 2006, includesdetailed system level simulations for a MIMO-OFDM system including theeffects of interference and hybrid ARQ. This prior work, though, doesnot allow cooperation between base stations and does not consider thespatial effects of interference.

What is needed, then, is an improved system and method that for linkadaptation that overcomes the above-described shortcomings in the priorart.

SUMMARY OF THE INVENTION

In accordance with one aspect, the present invention provides for asystem for wireless communication. The system includes a plurality ofbase transceiver stations each respective base transceiver stationhaving a plurality of antennas. The system further includes a pluralityof subscriber stations each respective subscriber station beingassociated with one of the base transceiver stations, and a networkconnecting the base transceiver stations. The system further includes aninterference schedule forward control channel carrying interferencetraining signals from a base transceiver station to an associatedsubscriber station, and an interference measurement reverse controlchannel carrying preferred transmission mode data from a subscriberstation to the associated base transceiver station.

In accordance with another aspect, the present invention provides for amethod for wireless communications. A signal is transmitted from a basestation to a subscriber station. The signal includes informationregarding an interferer. The method includes receiving the signal at thesubscriber station and using the information regarding an interferer toidentify a preferred spatial mode for subsequent transmissions to thesubscriber station. The method further includes transmitting thepreferred spatial mode from the subscriber station to the base station.

In accordance with yet another aspect, the present invention providesfor a communication protocol for a wireless communication network havinga plurality of base transceiver stations, each of the plurality of basetransceiver stations having associated therewith a respective pluralityof subscriber stations. The protocol provides for a networkinter-connecting the plurality base transceiver stations, aninterference schedule control channel whereby interferer information isfed from a respective base transceiver station to the respectiveplurality of subscriber stations associated therewith. The protocolfurther provides for an interference measurement control channel wherebypreferred transmission mode data is fed from each respective subscriberstation to the respective base station associated therewith, and whereinthe preferred transmission mode data is determined at least in part fromthe interferer information.

An advantageous feature of the present invention is the ability to feedforward to a subscriber station information regarding potentialinterference from neighboring base stations and to feed back from thesubscriber station a preferred spatial mode for subsequent transmissionsto the subscriber station, thus providing for a more robustcommunication system in which interference from other base stations iscompensated for.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present invention, and theadvantages thereof, reference is now made to the following descriptionstaken in conjunction with the accompanying drawings, in which:

FIG. 1 is a figure illustrating a wireless communication system with aplurality of antennas at the base station serving a plurality ofsubscriber stations;

FIG. 2A is a block diagram illustrating an idealized representation ofprior art base transceiver station functionality to support adaptivetransmission in a multiple antenna system;

FIG. 2B is a block diagram illustrating an idealized representation ofprior art subscriber station functionality to support adaptivetransmission in a multiple antenna system;

FIG. 3A illustrates three different spatial formatting techniques;

FIG. 3B is illustrates an exemplary spatial formatting table;

FIG. 4 is a block diagram illustrating an idealized representation ofthe components of a system in an embodiment of the present invention;

FIG. 5 is a block diagram illustrating an idealized representation ofthe components of a base transceiver station in an embodiment of thepresent invention;

FIG. 6 is a block diagram illustrating an idealized representation ofthe components of a subscriber station in an embodiment of the presentinvention;

FIG. 7A is a block diagram illustrating an exemplary spatial mode tablewith preferred modes employed in an embodiment of the present invention;

FIG. 7B is a block diagram illustrating an exemplary spatial mode tablewith rates recorded for each strategy illustrating example stepsexecuted to implement an embodiment of the present invention; and

FIG. 8 is flow chart illustrating exemplary steps executed to implementan embodiment of the present invention.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

The present invention will be described herein in the context of a MIMOwireless communication system. Those skilled in the art will recognizethat the inventive concepts described with reference to the preferredembodiments are limited to those described embodiments and can beextended to other embodiments, uses, and applications.

Well known elements are presented without detailed description in ordernot to obscure the present invention in unnecessary detail. For the mostpart, details unnecessary to obtain a complete understanding of thepresent invention have been omitted inasmuch as such details are withinthe skills of persons of ordinary skill in the relevant art. Detailsregarding control circuitry described herein are omitted, as suchcontrol circuits are within the skills of persons of ordinary skill inthe relevant art.

FIG. 1 is a block diagram illustrating an idealized cellularcommunication system. Base transceiver station (BTS) 100 (sometimes alsoreferred to as a base station) communicates with subscriber unit 105(sometimes also referred to as a subscriber station), which may bemobile or fixed, using wireless communication. Although only onesubscriber unit 105 is illustrated, it will be apparent to those skilledin the art that multiple subscriber units 105 will typically be employedin a typical wireless communication system. In the illustratedembodiment, BTS 100 communicates with subscriber unit 105 and a secondBTS 101 communicates with subscriber unit 107. Also illustratedschematically is the interference signal between BTS 100 and subscriberunit 107, and between BTS 101 and subscriber unit 105, respectively. BTS100, 101 each has a plurality of transmit antennas 125 while subscriberunits 105, 107 each has a plurality of receive antennas 130, for thepurpose of implementing what is known in the art as MIMO (multiple inputmultiple output) wireless communication. For clarity throughout thisdescription the term BTS will be used to refer to both a singular basetransceiver station and a to multiple base transceiver stations, themeaning being clear from the context. BTS 100 and 101 are connectedthrough what is known as a backhaul network 110. Backhaul network 110facilitates exchange of information between BTS and provides connectionto external networks such as the Internet and the Public SwitchedTelephone Network. A cell is the conventional term for the coverage areaof a BTS, such as cell 115 for BTS 100 and cell 116 for BTS 101.Subscriber units 105, 107 may experience co-channel interference fromother BTS that are transmitting on the same carrier frequency, as isillustrated by the dashed lines in FIG. 1. This phenomenon isparticularly pronounced along the edges or boundaries of a cell.

FIG. 2A is a block diagram illustrating an idealized prior art BTSsystem 100. Data 200, in the form of bits, symbols, or packets forexample, are processed by modulation and coding block 205 to convert totransmitted symbols and to add redundancy for the purpose of assistingwith error correction or error detection. The modulation and codingscheme is chosen based on input from the adaptive modulation controlblock 210. The output of modulation and coding block 205 is passed tospatial formatting block 220, which maps the input to multiple streamsof data for transmission on transmit antennas 125. Spatial formattingblock 220 may use any number of formatting methods known in the artincluding spatial multiplexing, space-time coding, delay diversity, theAlamouti code, double Alamouti space-time block code, precoding,beamforming, or the like. The choice of spatial formatting is also madeon a decision from the adaptive modulation control block 210. Inpreferred embodiments, the modulation, coding and spatial formattingdecisions are made jointly. Adaptive modulation control block 210 makesdecisions based on channel quality information 225. The channel qualityinformation input 225 may come from feedback from a subscriber unit,e.g. 105, to BTS 100 (see FIG. 1) or may be derived from measurementsmade at BTS 100. Channel quality information may, for purposes ofillustration, be in the form of quantized channel measurements,modulation, coding, and/or spatial formatting decisions, received signalstrength, signal-to-interference-plus-noise measurements, and the like.For example, the decision of modulation, coding, and spatial formattingmay be made based on space-time-frequency mean and variance ofpost-processing signal-to-noise ratio at the receiver. Adaptivemodulation control block 210 uses a spatial formatting table 215 whenusing channel quality information to make modulation, coding, andspatial formatting decisions. Spatial formatting table 215 may be alookup table indexed by channel quality information in one embodiment ormay be a mathematical function that uses the channel quality informationas an input to output a modulation, coding, and formatting decision.

FIG. 2B is a block diagram illustrating an idealized prior artsubscriber station system 105. Subscriber station (SS) 105 has aplurality of receive antennas 130 connecting through RF circuitry to aMIMO receiver signal processing block 250. Some of the key functionsperformed by MIMO receiver block 250 are channel estimation andestimation of signal-to-interference-plus-noise ratio (SINR). Channelestimation block 255 uses information inserted into the transmittedsignal in the form of training signals, training pilots, or structure inthe transmitted signal such as cyclostationarity to estimatecoefficients of the channel between BTS 100 and SS 105. Channelcoefficients are used by the MIMO receiver block 250 to help demodulatethe received signal. MIMO receiver signal processing block 250 alsoimplements an SINR measurement block in a preferred embodiment. In otherembodiments, the signal power, interference power, and noise power areestimated separately. The ability of the MIMO receiver signal processingblock 250 to correctly decode the transmitted data depends largely onthe channel and the SINR. Thus this information is input into generatechannel quality information block 265, which uses this information togenerate a channel quality information signal 225 that is sent back toBTS 100 for control of the adaptive modulation control block 210.

FIG. 3A is a diagram that illustrates three illustrative approaches forspatial formatting operations in block 220 (of FIG. 2A). In oneapproach, coded symbols 300 from modulation and coding block 205 areinput into a diversity encoder block 305. Diversity encoder 305 mayimplement any number of techniques known in the art, including theAlamouti code, space-time block code, space-time trellis code, delaydiversity, transmit beamforming, and the like. The diversity encoderprovides high reliability since the same coded information is sentacross all of the transmit antennas. In a second approach, coded symbolsfrom modulation and coding block 205 are input into a demultiplexer 320to produce two streams of data. These two data streams are input into ahybrid encoder 310, which maps them to four transmit antennas using anynumber of algorithms known in the art including transmit precoding ordouble alamout space-time block code. This is called a hybrid encoderbecause there is more than one stream but fewer streams input into thehybrid encoder than antennas fed by the hybrid encoder. In a thirdapproach, coded symbols from modulation and coding 205 are input into ademultiplexer 320 to produce four streams of data. These four streamsare input into a spatial multiplexing encoder 315, which maps them tofour transmit antennas directly or through some precoding means. Bysending four data streams, the multiplexing encoder 315 may achievehigher rate (sending more uncoded bits per channel use) than the hybridencoder but has more stringent channel and SINR requirements.

FIG. 3B illustrates an exemplary spatial formatting table 215. In thistable, an SINR estimate generated from block 260 (FIG. 2B) is used tochoose a column 355 in the table. Channel estimate from block 255 (FIG.2B) is used to determine if the channel is line-of-sight ornon-line-of-sight and has low spatial correlation or high spatialcorrelation. These parameters are used to choose the operating row 350.The entry of the table indicates a preferred spatial formatting fromamong the available approaches, e.g., the approaches illustrated in FIG.3A. Another table may indicate preferred modulation and coding or theseparameters may be stored jointly.

The challenge of spatial adaptation in cellular systems, which has notbeen properly addressed in the prior art, is the presence ofinterference. To explain this mathematically, consider narrowband MIMOcommunication systems, as are known in the art. The discrete-timereceived signals for a subscriber station 1 and a subscriber station 2may be writteny ₁ =H ₁₁ s ₁ +H ₂₁ s ₂ +v ₁y ₂ =H ₂₁ s ₁ +H ₂₂ s ₂ +v ₂

where y1 y2 are the received signal vectors of dimensions Nr×1, where Nris the number of receive antennas, s1 and s2 are the transmitted vectorsignals of dimension Nt×1 from base stations 1 and 2, where Nt is thenumber of transmit antennas at each base station. The Nr×Nt matrix Hkmrefers to the matrix channel between the kth receiver and the mthtransmitter. Finally, v1 and v2 are the vectors of additive noisecoefficients. For purposes of explanation it is assumed that the numberof transmit antennas at each base station is the same. Further, it isassumed that the number of receive antennas at each subscriber is alsothe same. It will be obvious to those skilled in the art how to makechanges as appropriate.

In the presence of interference, s1 and s2 influence the receivedsignals at both y1 and y2. Thus the decisions at one base stationinfluence the ability of the subscriber units to make their own spatialmodulation decisions. Thus prior work that neglected interference maynot perform well in the presence of interference.

One of the challenges of dealing with out-of-cell interference is thatunchecked interference will become what is called a competitive game.For example, suppose that at each time period, each base station updateshow it transmits its own signal as a function of what the interferingbase station previously sent. In this case the base stations willalternate transmission strategies, where each seeks to maximize its ownlink throughput without caring for the rate supported in the interferingbase station. This may require many iterations, which take time and thusmay not be practical in mobile channels, and further may not lead to afeasible solution.

Ideally, all the base stations would cooperate together, using what isknown as cooperative MIMO or network MIMO (see e.g. G. J. Foschini, H.Huang, K. Karakayali, R. A. Valenzuela, and S. Venkatesan, “The value ofcoherent base station coordination,” in Proc., Conference on InformationSciences and Systems (CISS), Johns Hopkins University, March 2005). Inthis concept, the base stations essentially get together and form asuper MIMO transmitter and receiver. Unfortunately, this requirescomplete collaboration between base stations. For example, base stationsmust exchange their sampled waveforms with this approach. This requiresan extremely high speed network backbone between base stations and doesnot seem feasible in most circumstances. Consequently, lower levels ofcooperation are needed to provide limited cooperation between basestations but not require complete exchange of transmit and receivesignals. A solution to this problem is described in the followingparagraphs. FIG. 4 provides an overview of the system components ofpreferred embodiments of this invention. In the system there are two ormore base transceiver station (BTS) 100 with a plurality of transmitantennas 125. BTS 100 communicates with a plurality of subscriberstations 105, which may be mobile or fixed, using wirelesscommunication. Subscriber station 105 has a plurality of antennas, forthe purpose of implementing MIMO wireless communication. The BTS 100 areconnected through backhaul network 110. Backhaul network 110 facilitatesexchange of information between BTS and provides connection to externalnetworks such as the Internet and the Public Switched Telephone Network.An interference schedule (IS) control channel 405 is used to communicateinformation about spatial formatting strategies of neighboring BTS tosubscriber stations 105. Subscriber stations 105 in response makemeasurements of their sensitivity to different interfering spatialformats and store this information in a spatial mode table (describedfurther below with reference to FIG. 6). The IS control channel 405 ispreferably a logical control channel used to convey information aboutthe spatial modes of the interfering base stations. Essentially, thebase transceiver station 105 gets as an input the schedules from theneighboring base transceivers stations, e.g., 107, which includes aspace/time/frequency mapping table and an index of the spatialtransmission strategy to be used for each transmission in the nexttransmission opportunity. Note that this information does notnecessarily include other information such as the destination user orthe rate, but this information may be included in some embodiments.

Base station 105 takes the information from neighboring base stationsand broadcasts this information to all the users. In some embodiments,the information is broadcast in tabular format, such as:

Mapping to PHY Spatial Transmission Method OFDM Symbol 1 MultiplexingOFDM Symbol 2 Diversity OFDM Symbol 3 Diversity OFDM Symbol 4 NotransmissionThe interference schedule feed forward control channel 405 may bebroadcast to all subscriber stations or may be multicast to selectsubscriber stations. The multicast option is useful in the cases whereusers are at different edges of the cell with different primaryinterfering base stations. The control channel can be mapped in anynumber of ways to the physical channel.

An interference measurement (IM) control channel 410 is used to conveyspatial mode tables from subscriber station 105 to BTS 100 in additionto channel quality information. A coordination channel (CC) 415 is usedto exchange spatial mode schedules between multiple BTS 100 for thepurpose of facilitating scheduling, producing information for the IScontrol channel 405, and interpreting data from the IM control channel410. Using the CC control channel 415, each BTS in the system canschedule users taking into account the sensitivity of subscriberstations 105 to different kinds of spatial formatting by interferingBTS, thus improving overall system performance.

FIG. 5 is a block diagram illustrating an idealized preferred embodimentBTS 100. Data 200, in the form of bits, symbols, or packets for example,are scheduled for transmission by scheduler 530, and forwarded tomodulation and coding block 205, then passed to the spatial formattingblock 220, followed by transmission on a plurality of antennas 125.Spatial formatting block 220 may use any number of formatting methodsknown in the art including spatial multiplexing, space-time blockcoding, space-time trellis coding, delay diversity, the Alamouti code,double Alamouti space-time block code, precoding, beamforming, transmitantenna selection, and the like. In preferred embodiments, themodulation, coding and spatial formatting decisions are made jointly.Various functional components of illustrated system are shown as blocksin, e.g., FIGS. 5 and 6. One skilled in the art will recognize thatthese logical/functional blocks are for illustration only and that in anactual implementation, the various illustrated blocks may be realized asspecial purpose hardware, general purpose hardware running appropriateinstructions sets, software commands, firmware commands, programmablelogic, and combinations of the like.

Modulation and coding block 205 may perform any number of coding andmodulation techniques including quadrature amplitude modulation, phaseshift keying, frequency shift keying, differential phase modulation,convolutional coding, turbo coding, bit interleaved convolutionalcoding, low density parity check coding, fountain coding; or blockcoding. Other techniques may also be employed.

The rate chosen for transmission by modulation and coding block 205 andthe choice of spatial formatting 220 is determined, at least in part, bycoordinated link adaptation block 500. The inputs to coordinated linkadaptation block 500 are scheduling decisions from scheduler block 530,spatial mode schedules 520 from interfering base stations receivedthrough coordination control channel 415, and channel qualityinformation from channel quality information block 515 derived from IMcontrol channel 410. In another preferred embodiment, scheduling,modulation, coding, and spatial formatting decisions are made jointly.The spatial formatting information for the scheduled users is output tothe coordination control channel 415 and delivered to other BTS 100.This information allows BTS to coordinate their transmission schedulesbased on sensitivity of neighboring users to different spatialformatting methods. While not explicitly illustrated, it is obvious tothose skilled in the art that OFDM (orthogonal frequency divisionmultiplexing) modulation can be used. Further, any number of multipleaccess techniques could be used including but not limited to orthogonalfrequency division multiple access; code division multiple access;frequency division multiple access; or time division multiple access.The multiple access technique may be combined with the modulation andcoding 205 or the spatial formatting 220 blocks among others.

Scheduler 530 makes decisions about which among one or more users arechosen for transmission. Scheduler 530 may use any of the knownscheduling disciplines in the literature including round robin, maximumsum rate, proportional fair, minimum remaining processing time, ormaximum weighted sum rate. The actions of scheduler 530 are coordinatedthrough multi-base schedule block 525. In one embodiment, neighboringBTS 100 take turns in being the lead BTS. The lead BTS makes schedulingdecisions locally and reports the spatial formatting methods to be usedby its scheduler users to other BTS through coordination control channel415. Neighboring BTS then make their scheduling decisions in response tothe kind of interference that will be generated by the lead BTS. Inanother preferred embodiment, multiple BTS make scheduling decisionsjointly to maximize some joint performance metric.

Spatial mode schedules 520 are possibly compressed in compute rateallocation summary block 510 and broadcast, multicast, or unicast to thesubscriber stations 105 through the IS control channel 405.Specifically, information about the interference spatial formatting tobe expected by out-of-cell interference is contained in IS controlchannel 405.

Subscriber units return their respective sensitivity to differentspatial formatting modes through IM control channel 410. Channel qualityinformation is extracted from IM 410 in channel quality informationblock 515 as well as other information that can be used by the scheduler530 and coordinated link adaptation block 500 to make schedulingdecisions.

FIG. 6 is a block diagram illustrating an idealized preferred embodimentsubscriber station 105. Subscriber station 105 has a plurality ofreceive antennas 130, connecting through RF circuitry (not shown) to aMIMO receiver signal processing block 250. Some of the key functionsperformed by MIMO receiver signal processing block 250 are channelestimation, signal quality estimation, and interference estimation.Inputs from channel estimation block 255, signal quality estimationblock 600, and interference estimation block 605 are used to computespatial mode table 610 along with the interference schedule informationderived from IS control channel 405 sent by BTS 100. Inputs from channelestimation block 255, signal quality estimation block 600, andinterference estimation block 605 are also used to compute channelquality information 615. Both the spatial mode table 610 and channelquality information 615 are packaged into IM control channel 410 anddelivered back to base station 100.

Channel estimation block 255 may employ any number algorithms known inthe art including least squares, maximum likelihood, maximum aposteriori, Bayes estimator, adaptive estimator, blind estimator, amongothers. Some algorithms exploit known information inserted into thetransmitted signal in the form of training signals or training pilots,while others use structure in the transmitted signal such ascyclostationarity to estimate coefficients of the channel between a BTSand a subscriber station.

Estimate interference block 605 estimates some measure of theinterference. In one embodiment, this block estimates the totalinterference power. In another preferred embodiment spatial correlationmatrix of the interferer is estimated. In yet another preferredembodiment, block 605 estimates the total spatial correlation matrix ofthe received signal and subtracts out the spatial correlation due to theestimated channel and the estimated noise power. This task can beaccomplished using techniques and algorithms that will be apparent toone skilled in the art as informed by the teachings contained herein androutine experimentation.

Estimate signal quality block 600 outputs some measure of performancecorresponding to the desired signal. In one embodiment this estimateconsists of a received signal power estimate. In another embodiment,block 600 provides an estimate of the received signal-to-noise ratio. Inyet another embodiment, block 600 provides an estimate of the averagereceived signal power, averaged over subcarriers in an OFDM system. Thistask can be accomplished using techniques and algorithms that will beapparent to one skilled in the art as informed by the teachingscontained herein and routine experimentation.

Channel quality estimate block 615 provides information about theability of a subscriber station to correctly decode the transmittedsignal. There are many different functions that can be used by BTS 100in scheduling and transmission decisions. For example, channel qualityestimate block 615 may quantize an estimate of the channel in oneembodiment. In another embodiment this block may compute some functionof the estimated channel such as the norm of the channel matrix,singular values of the channel matrix, or average singular values of thechannel matrix. Block 615 may also use the output of signal qualityestimate block 600 to compute a measure such as thesignal-to-interference-plus-noise ratio or the post-processingsignal-to-interference-plus-noise ratio. Other information such ascyclic redundancy checks may be used to compute an estimate of thepacket error rate in yet another embodiment.

Compute spatial mode table 610 determines the sensitivity of thesubscriber to the spatial formatting currently being employed by aninterferer (e.g. a neighboring BTS). Consider as an example the casewhere a subscriber station experiences interference from one dominantinterfering BTS. The choice of spatial formatting used by theinterfering BTS impacts the choice of spatial formatting for thatsubscriber. For example, it is well known from basic array processingtheory that the number of signals that can be decoded using conventionallinear array processing is a function of the number of receive antennas.Spatial multiplexing creates multiple signals that must all be decodedwhile transmit beamforming creates only a single signal that must bedecoded. Thus if the interfering base station employs transmitbeamforming, it is more likely that a spatial formatting approach thatsupports multiple streams, such as hybrid or spatial multiplexing, willwork well for that subscriber station. Of course, this depends on thepropagation environment. For example, if a subscriber station does notsee significant interference power from an interfering base station thenthe subscriber station will not be sensitive to the spatial formattingemployed by the interfering base station. As another example, thepropagation channel between the interfering base station and thesubscriber may be poorly conditioned. This means that signals arrivingfrom the interfering base station are highly correlated. Thus even ifthe interfering base station uses a spatial formatting technique likespatial multiplexing, the subscriber station may be less sensitive tothe spatial formatting method employed. It will be clear to thoseskilled in the art that spatial formatting methods that send fewsubstreams create an interference signal that is highly correlated. Itis also clear to those skilled in the art that a channel between theinterfering base station and the subscriber that is not well conditionedwill also create an interfering signal that is highly correlated. Thepreferred embodiments of the present invention is preferably able todistinguish these two cases thanks to the interference schedule controlchannel 405, which is broadcast from the BTS.

Interference schedule control channel 405 informs all the appropriatesubscribers about the transmission plans of neighboring and thusinterfering BTS. In a preferred embodiment, the interference schedulecontrol channel 405 carries information about the interfering spatialmode schedules for one or more neighboring base stations. In thisembodiment, a table may be broadcast for each interfering BTS thatindicates the planned spatial formatting technique in eachtime/frequency allocation. In another preferred embodiment, theinterference schedule control channel 405 carries compressed spatialmode schedules for one or more neighboring base stations. In this casethe table may be compressed using a data compression algorithm known tothose skilled in the art. It is clear to those skilled in the art thatthe interference schedule control channel 405 can be implemented as alogical control channel or as a physical control channel.

The spatial mode table computation block 610 determines the sensitivityof the subscriber station to the spatial formatting mode employed by theinterferer. For this purpose, during each time/frequency transmission,block 610 uses information from interference schedule control channel405 to determine the spatial formatting employed by the interferer. Itthen applies an algorithm to estimate the highest rate transmissionstrategy that may be employed in the current estimated channel assumingthe interferer uses the same spatial formatting strategy.

In a preferred embodiment, the spatial mode table records the preferredmodulation, coding, and spatial formatting based on the current channelestimate conditioned on the interference spatial formatting strategy. Inanother embodiment, the spatial mode table records just the preferredspatial formatting strategy conditioned on an interfering spatialformatting strategy. In yet another embodiment, the spatial mode tablerecords the rate achieved for each spatial formatting strategy possible.

Spatial formatting table block 610 may accumulate multiple observationsand combine them to improve the quality of the spatial mode table. Itmay also reset from time-to-time to compensate for changing channel andinterference conditions.

To use interference schedule control channel 405, the subscriber stationmust know the source of interfering BTS. In a preferred embodiment,interfering BTS are obtained through the handoff search process, wherethe subscriber measures the pilots of neighboring BTS. In anotherembodiment, geographic location methods such as GPS or the like are usedto determine the subscriber station location and thus the most likelyinterfering BTS.

FIG. 7A illustrates a preferred embodiment the spatial mode table 700,which is used in compute spatial mode table block 610. In this example,there are two spatial modes 705, a beamforming mode and a spatialmultiplexing mode. A single strong interferer is assumed. Optionallythere is also a no transmission option. Based on inputs from channelestimation block 255, signal quality estimation block 600, andinterference estimation block 605, the preferred spatial modeconditioned on the interfering mode is calculated and stored in thetable. Many observations may be averaged or otherwise combined todetermine the preferred mode. Although a single strong interfering basestation is illustrated for purpose of this discussion, one skilled inthe art will recognize that the teachings contained herein can bereadily extended to, e.g., other interferers in the wireless network,two or more interfering base stations, and the like.

FIG. 7B illustrates another preferred embodiment spatial mode table 710,which is used in compute spatial mode table block 610. In this example,there are two spatial modes 705 a beamforming mode and a spatialmultiplexing mode. A single strong interferer is assumed. Optionallythere is also a no transmission option. Based on inputs from channelestimation block 255, signal quality estimation block 600, andinterference estimation block 605, the preferred modulation and also thepreferred coding rate for each spatial transmission format is recordedin the table. Many observations may be averaged or otherwise combined todetermine the preferred mode.

FIG. 8 illustrates a preferred embodiment computational flow chart,which is used in compute spatial mode table block 610. In this example,the channel is first estimated 800. Then the spatial covariance matrixof the interference is derived from the spatial covariance of the totalsignal in 805. A spatial whitening filter is derived from theinterference plus noise covariance matrix in 810. The expected ratecorresponding to the whitened channel is computed in 815. The achievablerate is then recorded as appropriate in the spatial mode table in 820.There are two spatial modes: a beamforming mode and a spatialmultiplexing mode. Again, a single strong interferer is assumed, butthis is not a limitation on the illustrated technique. Optionally thereis also a no transmission option. Based on inputs from channelestimation block 255, signal quality estimation block 600, andinterference estimation block 605, the preferred modulation and codingrate for each spatial transmission format is recorded in the table. Manyobservations may be averaged or otherwise combined to determine thepreferred mode.

The computational flowchart 800 of FIG. 8 may be explained throughmathematical equations in the following preferred embodiment. For anarrowband MIMO communication system, the signal at the subscriber 105in discrete-time may be written asy=Hx+v _(I) +v

where H is the channel, x is the transmitted signal vector, v_(I) is theinterfering signal vector and v is noise. In step 800, the channel H isestimated using any number of algorithms known in the art. Using channelH, the next step is to compute the total signal covariance matrixRy=Eyy* where * is conjugate transpose. This may be done in the usualway using a sample average. Then the interference covariance matrixRv_(I)=Ev_(I)v_(I)* can be computed as Rv_(I)=Ry−HRxH*+Rv where Rx isthe covariance matrix of the transmitted vector x (determined from thespatial formatting matrix) and Rv is the noise covariance matrix. Then aspatial whitening filter in 810 is derived from Rv_(I)+Rv by computingthe Cholesky decomposition for example. This is written as Rv_(I)^(1/2). Then the whitening filter is applied to the received signal toproduce Rv_(I) ^(1/2)y=Rv_(I) ^(1/2)Hx+Rv_(I) ^(1/2)v_(I)+Rv_(I) ^(1/2)vwhere Rv_(I) ^(1/2)H is the whitened channel and Rv_(I) ^(1/2)(v_(I)+v)is the whitened noise. The expected rate in 815 is computed from thewhitened channel and the whitened interference plus noise term. Forexample, it could be computed using Shannon's formula as log(I+Rv_(I)^(1/2)HRx(I+Rv_(I)R_(v))⁻¹H*Rv_(I) ^(1/2)*) in one embodiment. Thespatial mode table can then be updated accordingly.

Although the present invention and its advantages have been described indetail, it should be understood that various changes, substitutions andalterations can be made herein without departing from the spirit andscope of the invention as defined by the appended claims. Moreover, thescope of the present application is not intended to be limited to theparticular processes, algorithms, methods and steps described in thespecification. As one of ordinary skill in the art will readilyappreciate from the disclosure of the present invention, processes,machines, means, methods, or steps, presently existing or later to bedeveloped, that perform substantially the same function or achievesubstantially the same result as the corresponding embodiments describedherein may be utilized according to the present invention. Accordingly,the appended claims are intended to include within their scope suchprocesses, machines, means, methods, or steps.

What is claimed is:
 1. A method for wireless communications comprising:receiving, by a subscriber station from a base station, spatial modescheduling information regarding an interferer to the subscriberstation; performing a channel estimation on a received signal receivedby the subscriber station, the received signal including an interferencesignal from the interferer in accordance with the spatial modescheduling information; deriving a spatial whitening filter inaccordance with the interference signal; applying the spatial whiteningfilter to the received signal; determining an expected rate inaccordance with the spatial whitening filter applied-received signal foreach of a plurality of interfering spatial modes of the interferer;identifying, in accordance with each respective expected rate, apreferred spatial mode for each of the plurality of interfering spatialmodes of the interferer, for subsequent transmissions to the subscriberstation; and transmitting, from the subscriber station to the basestation, a spatial mode table comprising each respective preferredspatial mode for each of the plurality of interfering spatial modes ofthe interferer.
 2. The method of claim 1, further comprising: receiving,by the subscriber station from the base station, transmissions scheduledin accordance with the preferred spatial mode.
 3. The method of claim 1,wherein using the spatial mode scheduling information regarding theinterferer at the subscriber station to identify the preferred spatialmode comprises: performing a signal quality estimation on the receivedsignal; and performing an interference estimation on the receivedsignal.
 4. The method of claim 3 wherein: performing the channelestimation includes employing a first algorithm to estimate coefficientsof a channel between the base station and the subscriber station, thefirst algorithm selected from the group consisting of least squares,maximum likelihood, maximum a posteriori, Bayes estimator, adaptiveestimator, and blind estimator; performing the signal quality estimationincludes estimating a characteristic of the received signal selectedfrom the group consisting of signal power, signal-to-noise ratio,average signal power, signal strength, signal-to-noise ratio (SNR),signal-to-interference-plus-noise ratio (SINR), quantized channel stateinformation, limited feedback channel state information, and channelcorrelation; and performing the interference estimation on the receivedsignal includes estimating a measure of interference selected from thegroup consisting of total interference power, a spatial correlationmatrix of the interferer, and total spatial correlation matrix of thereceived signal less a spatial correlation due to the estimated channeland estimated noise power.
 5. The method of claim 1, wherein thepreferred spatial mode is selected from the group consisting of spatialmultiplexing, space-time block coding, space-time trellis coding,transmit beamforming, transmit precoding, delay diversity, Alamouticode, double Alamouti space-time block code, closed loop MIMO, andtransmit antenna selection.
 6. The method of claim 1 further comprising:using the spatial mode scheduling information regarding the interfererto identify a preferred coding rate; and transmitting the preferredcoding rate from the subscriber station to the base station.
 7. Themethod of claim 1, further comprising: transmitting, by the subscriberstation to the base station, a preferred coding rate in accordance withthe spatial mode scheduling information regarding the interferer.
 8. Themethod of claim 1, wherein: the receiving comprises receiving thereceived signal including the spatial mode scheduling information on aninterference schedule feed forward control channel, and the transmittingcomprises transmitting the preferred spatial mode on an interferencemeasurement control channel.
 9. The method of claim 1, wherein thespatial mode scheduling information is a compressed spatial modeschedule for the interferer.
 10. The method of claim 1, furthercomprising transmitting a preferred modulation and a preferred codingrate in addition to the preferred spatial mode.
 11. A method forwireless communications comprising: transmitting, by a base station to asubscriber station, spatial mode scheduling information regarding aninterferer to the subscriber station; transmitting a transmitted signalto the subscriber station, the transmitted signal and an interferencesignal from the interferer forming a total signal for the subscriberstation to use in performing a channel estimation in accordance with thespatial mode scheduling information, deriving a spatial whitening filterin accordance with the interference signal; applying the spatialwhitening filter to the total signal; and determining an expected ratein accordance with the spatial whitening filter-applied total signal foreach of a plurality of interfering spatial modes of the interferer;receiving, by the base station from the subscriber station, a spatialmode table comprising a respective preferred spatial mode for each ofthe plurality of interfering spatial modes of the interferer, inaccordance with each respective expected rate; and schedulingtransmissions from the base station to the subscriber station using thespatial mode table received from the subscriber station.
 12. The methodof claim 11 wherein the preferred spatial mode is selected from thegroup consisting of spatial multiplexing, space-time block coding,space-time trellis coding, transmit beamforming, transmit precoding,delay diversity, Alamouti code, double Alamouti space-time block code,closed loop MIMO, and transmit antenna selection.
 13. The method ofclaim 11 further comprising: receiving, by the base station from thesubscriber station, a preferred coding rate in accordance with thespatial mode scheduling information regarding the interferer.
 14. Themethod of claim 11 further comprising: transmitting from the basestation to a second base station scheduling information based at leastin part on the preferred spatial mode received from the subscriberstation.
 15. The method of claim 11 further comprising: transmitting, bythe base station to the subscriber station, transmissions scheduled inaccordance with the preferred spatial mode.
 16. The method of claim 11,wherein: the transmitting the spatial mode scheduling informationcomprises transmitting the spatial mode scheduling information on aninterference schedule feed forward control channel; and the receivingcomprises receiving the preferred spatial mode on an interferencemeasurement control channel.
 17. The method of claim 11, furthercomprising, prior to the transmitting the spatial mode schedulinginformation, receiving, by the base station from the interferer, thespatial mode scheduling information.
 18. The method of claim 11, whereinthe spatial mode scheduling information indicates planned spatialformatting techniques to be used in time/frequency allocations by theinterferer.
 19. The method of claim 11, further comprising receiving apreferred modulation and a preferred coding rate in addition to thepreferred spatial mode.